Objective: To provide a model for prospective budgeting for home care that is plausible, coherent, flexible, and sufficiently tractable that it can serve as a template for practical decision making and to clarify what would be the data requirements and statistical framework to calibrate the model.
Methods: Methods used are standard risk-neutral expected value theory, cost benefit analysis, and the conditional logistic probability model.
Results: A simple but effective prospective budgeting model that provides analytic scaffolding for a practical decision support system for home care case managers, consultants, and program evaluators that can improve program equity, efficiency, and effectiveness.